DESCRIPTION: The objective of this project is to develop, evaluate, and apply efficient methodologies for the resolution of genetic determinants, and to investigate how genes and environments act together to produce complex diseases and complex disease-related traits. The specific aims involve theoretical/methodological studies in path, segregation, and linkage analysis, with an emphasis on combined models, non-parametric linkage methods, and optimal strategies for detecting genetic determinants of complex traits. Both simulation studies and analysis of actual family data will be performed to assess the applicability and practical utility of the methods. The methodological issues to be addressed include extensions of combined segregation-path analysis models to include multivariate traits, oligogenic models, and marker data; extensions of combined path, segregation, and linkage analyses based on regressive models; development of an oligogenic multivariate model for segregation/linkage analysis with multiple markers using a variance component approach; extensions of sib-pair methods to incorporate multipoint IBD distributions and multivariate traits; development of meta-analysis and optimal designs for sip-pair linkage tests; extensions of quantitative trait locus methods to incorporate genotype by environment interactions; and improved computational algorithms using parallel processing. Simulation studies are proposed to evaluate merits and pitfalls associated with various theoretical models and to evaluate those methodological issues that are analytically intractable (e.g. the evaluation of power to detect gene-environment interactions). Maximum likelihood methods and likelihood inference will be the focus of most of the testing procedures and hypothesis generation.